Genetic control and phenotypic characterization of panicle architecture and grain yield-related traits in foxtail millet (Setaria italica)

Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS

KEY MESSAGE

Eleven QTLs for agronomic traits were identified by RTM- and MLM-GWAS, putative candidate genes were predicted and two markers for grain weight were developed and validated. Foxtail millet (Setaria italica), the second most cultivated millet crop after pearl millet, is an important grain crop in arid regions. Seven agronomic traits of 408 diverse foxtail millet accessions from 15 provinces in China were evaluated in three environments. They were clustered into two divergent groups based on genotypic data using ADMIXTURE, which was highly consistent with their geographical distribution. Two models for genome-wide association studies (GWAS), namely restricted two-stage multi-locus multi-allele (RTM)-GWAS and mixed linear model (MLM)-GWAS, were used to dissect the genetic architecture of the agronomic traits based on 13,723 SNPs. Eleven quantitative trait loci (QTLs) for seven traits were identified using two models (RTM- and MLM-GWAS). Among them, five were considered stable QTLs that were identified in at least two environments using MLM-GWAS. One putative candidate gene (SETIT_006045mg, Chr4: 744,701-746,852) that can enhance grain weight per panicle was identified based on homologous gene comparison and gene expression analysis and was validated by haplotype analysis of 330 accessions with high-depth (10×) resequencing data (unpublished). In addition, homologous gene comparison and haplotype analysis identified one putative foxtail millet ortholog (SETIT_032906mg, Chr2: 5,020,600-5,029,771) with rice affecting the target traits. Two markers (cGWP6045 and kTGW2906) were developed and validated and can be used for marker-assisted selection of foxtail millet with high grain weight. The results provide a fundamental resource for foxtail millet genetic research and breeding and demonstrate the power of integrating RTM- and MLM-GWAS approaches as a complementary strategy for investigating complex traits in foxtail millet.

Multi-environment GWAS identifies genomic regions underlying grain nutrient traits in foxtail millet (Setaria italica)

KEY MESSAGE

A total of 104 foxtail millet accessions were evaluated for 11 nutrients in three environments and 67 high-confidence marker-trait associations (MTAs) were identified. Six SNPs showed pleiotropic effect and associated with two or more nutrients, whereas 24 candidate genes were identified for 28 MTAs involving seven traits. Millets are known for their better nutritional profiles compared to major cereals. Foxtail millet (Setaria italica) is rich in nutrients essential to circumvent malnutrition and hidden hunger. However, the genetic determinants underlying this trait remain elusive. In this context, we evaluated 104 diverse foxtail millet accessions in three different environments (E1, E2, and E3) for 11 nutrients and genotyped with 30K SNPs. The genome-wide association study showed 67 high-confidence (Bonferroni-corrected) marker-trait associations (MTAs) for the nutrients except for phosphorus. Six pleiotropic SNPs were also identified, which were associated with two or more nutrients. Around 24 candidate genes (CGs) were identified for 28 MTAs involving seven nutrients. A total of 17 associated SNPs were present within the gene region, and five (5) were mapped in the exon of the CGs. Significant SNPs, desirable alleles and CGs identified in the present study will be useful in breeding programmes for trait improvement.

Mapping of major QTL and candidate gene analysis for hull colour in foxtail millet (Setaria italica (L.) P. Beauv.)

BACKGROUND

Hull colour is an important morphological marker for selection in seed production of foxtail millet. However, the molecular mechanisms underlying hull colour variation remain unknown.

RESULTS

An F7 recombinant inbred line (RIL) population containing 215 lines derived from Hongjiugu × Yugu18 was used to analyze inheritance and detect the quantitative trait loci (QTL) for four hull colour traits using major gene plus polygene mixed inheritance analysis and composite interval mapping (CIM) in four environments. Genetic analysis revealed that the hull colour L* value (HCL*) was controlled by two major genes plus additive polygenes, the hull colour a* value (HCa*) was controlled by three major genes, the hull colour b* value (HCb*) was controlled by two major genes plus polygenes, and the hull colour C* value (HCC*) was controlled by four major genes. A high-density genetic linkage map covering 1227.383 cM of the foxtail millet genome, with an average interval of 0.879 cM between adjacent bin markers, was constructed using 1420 bin markers. Based on the genetic linkage map and the phenotypic data, a total of 39 QTL were detected for these four hull colour traits across four environments, each explaining 1.50%-49.20% of the phenotypic variation. Of these, six environmentally stable major QTL were co-localized to regions on chromosomes 1 and 9, playing a major role in hull colour. There were 556 annotated genes within the two QTL regions. Based on the functions of homologous genes in Arabidopsis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) gene annotations, five genes were predicted as candidate genes for further studies.

CONCLUSIONS

This is the first study to use an inheritance model and QTL mapping to determine the genetic mechanisms of hull colour trait in foxtail millet. We identified six major environmentally stable QTL and predicted five potential candidate genes to be associated with hull colour. These results advance the current understanding of the genetic mechanisms underlying hull colour traits in foxtail millet and provide additional resources for application in genomics-assisted breeding and potential isolation and functional characterization of the candidate genes.

QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome

As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 metabolites via with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including Sd1 semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as Sd1, were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted breeding.

Revitalization of small millets for nutritional and food security by advanced genetics and genomics approaches

Small millets, also known as nutri-cereals, are smart foods that are expected to dominate food industries and diets to achieve nutritional security. Nutri-cereals are climate resilient and nutritious. Small millet-based foods are becoming popular in markets and are preferred for patients with celiac and diabetes. These crops once ruled as food and fodder but were pushed out of mainstream cultivation with shifts in dietary habits to staple crops during the green revolution. Nevertheless, small millets are rich in micronutrients and essential amino acids for regulatory activities. Hence, international and national organizations have recently aimed to restore these lost crops for their desirable traits. The major goal in reviving these crops is to boost the immune system of the upcoming generations to tackle emerging pandemics and disease infestations in crops. Earlier periods of civilization consumed these crops, which had a greater significance in ethnobotanical values. Along with nutrition, these crops also possess therapeutic traits and have shown vast medicinal use in tribal communities for the treatment of diseases like cancer, cardiovascular disease, and gastrointestinal issues. This review highlights the significance of small millets, their values in cultural heritage, and their prospects. Furthermore, this review dissects the nutritional and therapeutic traits of small millets for developing sustainable diets in near future.

The Integration of Genome-Wide Association Study and Homology Analysis to Explore the Genomic Regions and Candidate Genes for Panicle-Related Traits in Foxtail Millet

Panicle traits are important factors affecting yield, and their improvement has long been a critical goal in foxtail millet breeding. In order to understand the genetic basis of panicle formation, a large-scale genome-wide association study (GWAS) was performed in this study for six panicle-related traits based on 706,646 high-polymorphism SNP loci in 407 accessions. As a result, 87 quantitative trait loci (QTL) regions with a physical distance of less than 100 kb were detected to be associated with these traits in three environments. Among them, 27 core regions were stably detected in at least two environments. Based on rice-foxtail millet homologous comparison, expression, and haplotype analysis, 27 high-confidence candidate genes in the QTL regions, such as Si3g11200 (OsDER1), Si1g27910 (OsMADS6), Si7g27560 (GS5), etc., affected panicle-related traits by involving multiple plant growth regulator pathways, a photoperiod response, as well as panicle and grain development. Most of these genes showed multiple effects on different panicle-related traits, such as Si3g11200 affecting all six traits. In summary, this study clarified a strategy based on the integration of GWAS, a homologous comparison, and haplotype analysis to discover the genomic regions and candidate genes for important traits in foxtail millet. The detected QTL regions and candidate genes could be further used for gene clone and marker-assisted selection in foxtail millet breeding.

Genome-wide identification of quantitative trait loci for morpho-agronomic and yield-related traits in foxtail millet (Setaria italica) across multi-environments

Foxtail millet (Setaria italica) is an ideal model of genetic system for functional genomics of the Panicoideae crop. Identification of QTL responsible for morpho-agronomic and yield-related traits facilitates dissection of genetic control and breeding in cereal crops. Here, based on a Yugu1 × Longgu7 RIL population and genome-wide resequencing data, an updated linkage map harboring 2297 bin and 74 SSR markers was constructed, spanning 1315.1 cM with an average distance of 0.56 cM between adjacent markers. A total of 221 QTL for 17 morpho-agronomic and yield-related traits explaining 5.5 ~ 36% of phenotypic variation were identified across multi-environments. Of these, 109 QTL were detected in two to nine environments, including the most stable qLMS6.1 harboring a promising candidate gene Seita.6G250500, of which 70 were repeatedly identified in different trials in the same geographic location, suggesting that foxtail millet has more identical genetic modules under the similar ecological environment. One hundred-thirty QTL with overlapping intervals formed 22 QTL clusters. Furthermore, six superior recombinant inbred lines, RIL35, RIL48, RIL77, RIL80, RIL115 and RIL125 with transgressive inheritance and enrichment of favorable alleles in plant height, tiller, panicle morphology and yield related-traits were screened by hierarchical cluster. These identified QTL, QTL clusters and superior lines lay ground for further gene-trait association studies and breeding practice in foxtail millet.